* Fix TypeError: Object of type int64 is not JSON serializable
* Convert numpy.float64 and numpy.int64 to float and int for json serialization
* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py
* * make style
* Squash 88 commits
* Use markdown
* Remove mdx files due to bad rebase
* Fix modeling files due to bad rebase
* Fix style
* Update comment
* fix
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* let's go!
* initial implementation of token-level timestamps
* only return a single timestamp per token
* remove token probabilities
* fix return type
* fix doc comment
* strip special tokens
* rename
* revert to not stripping special tokens
* only support models that have alignment_heads
* add integration test
* consistently name it token-level timestamps
* small DTW tweak
* initial support for ASR pipeline
* fix pipeline doc comments
* resolve token timestamps in pipeline with chunking
* change warning when no final timestamp is found
* return word-level timestamps
* fixup
* fix bug that skipped final word in each chunk
* fix failing unit tests
* merge punctuations into the words
* also return word tokens
* also return token indices
* add (failing) unit test for combine_tokens_into_words
* make combine_tokens_into_words private
* restore OpenAI's punctuation rules
* add pipeline tests
* make requested changes
* PR review changes
* fix failing pipeline test
* small stuff from PR
* only return words and their timestamps, not segments
* move alignment_heads into generation config
* forgot to set alignment_heads in pipeline tests
* tiny comment fix
* grr
* Fix saved_model_creation_extended
* Skip the BLIP model creation test for now
* Fix TF SAM test
* Fix longformer tests
* Fix Wav2Vec2
* Add a skip for XLNet
* make fixup
* make fix-copies
* Add comments
* Fix one BLIP arg not being optional, remove misspelled arg
* Remove the lxmert test overrides and just use the base test_saved_model_creation
* saved_model_creation fixes and re-enabling tests across the board
* Remove unnecessary skip
* Stop caching sinusoidal embeddings in speech_to_text
* Fix transfo_xl compilation
* Fix transfo_xl compilation
* Fix the conditionals in xglm
* Set the save spec only when building
* Clarify comment
* Move comment correctly
* Correct embeddings generation for speech2text
* Mark RAG generation tests as @slow
* Remove redundant else:
* Add comment to clarify the save_spec line in build()
* Fix size tests for XGLM at last!
* make fixup
* Remove one band_part operation
* Mark test_keras_fit as @slow
* Revert whisper change and modify the test_compile_tf_model test
* make fixup
* Tweak test slightly
* Add functional model saving to test
* Ensure TF can infer shapes for data2vec
* Add override for efficientformer
* Mark test as slow
* Stop storing references to bound methods in tf.functions
* Remove the gc.collect calls now that we resolved the underlying problem
* Remove the default signature from model.serving entirely, big cleanup
* Remove _prune_signature as self.input_signature can prune itself
* Restore serving docstring
* Update int support test to check the input signature
* Make sure other tests also use model.input_signature and not serving.input_signature
* Restore _prune_signature
* Remove the doctest GC now it's no longer needed
* Correct core tests to use the pruned sig
* order lines correctly in core tests
* Add eager_serving back with a deprecation warning
* Fix model load when it has both code on the Hub and locally
* Add input check with timeout
* Add tests
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Some non-saved stuff
* Add feature extractors
* Add image processor
* Add model
* Add processor and tokenizer
* Reduce timeout
---------
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* A fun new PR where I break the entire codebase again
* A fun new PR where I break the entire codebase again
* Handle cross-attention
* Move calls to model(model.dummy_inputs) to the new build() method
* Seeing what fails with the build context thing
* make fix-copies
* Let's see what fails with new build methods
* Fix the pytorch crossload build calls
* Fix the overridden build methods in vision_text_dual_encoder
* Make sure all our build methods set self.built or call super().build(), which also sets it
* make fix-copies
* Remove finished TODO
* Tentatively remove unneeded (?) line
* Transpose b in deberta correctly and remove unused threading local
* Get rid of build_with_dummies and all it stands for
* Rollback some changes to TF-PT crossloading
* Correctly call super().build()
* Add test_backbone for convnext
* Add TimmBackbone model
* Add check for backbone type
* Tidying up - config checks
* Update convnextv2
* Tidy up
* Fix indices & clearer comment
* Exceptions for config checks
* Correclty update config for tests
* Safer imports
* Safer safer imports
* Fix where decorators go
* Update import logic and backbone tests
* More import fixes
* Fixup
* Only import all_models if torch available
* Fix kwarg updates in from_pretrained & main rebase
* Tidy up
* Add tests for AutoBackbone
* Tidy up
* Fix import error
* Fix up
* Install nattan in doc_test_job
* Revert back to setting self._out_xxx directly
* Bug fix - out_indices mapping from out_features
* Fix tests
* Dont accept output_loading_info for Timm models
* Set out_xxx and don't remap
* Use smaller checkpoint for test
* Don't remap timm indices - check out_indices based on stage names
* Skip test as it's n/a
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleaner imports / spelling is hard
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
